Leveraging Existing Data and Analytic Methods for Health Disparities Research Related to Aging and Alzheimer's Disease and Related Dementias (ADRD)

利用现有数据和分析方法进行与衰老和阿尔茨海默氏病及相关痴呆症 (ADRD) 相关的健康差异研究

• 批准号: 10224101
• 负责人: IGOR AKUSHEVICH
• 金额: $ 5万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10224101
• 关键词: Academic Medical Centers; Address; Aging; Alzheimer' s Disease; Alzheimer' s disease related dementia; Area; Caring; Clinic; Clinical; Clinical Data; Collaborations; Communities; Complex; Data; Data Analyses; Data Analytics; Data Set; Databases; Dependence; Development; Diffuse; Diffusion; Discipline; Disease; Educational workshop; Epidemiology; Ethics; Ethnic Origin; Future; Generations; Genetic; Geographic Locations; Goals; Health; Health Services Accessibility; Healthcare Systems; Hospitals; Individual; Interdisciplinary Study; Intervention; Knowledge; Machine Learning; Measures; Medical; Medical Care Costs; Medical center; Medicare; Medicare claim; Methodology; Methods; Modeling; Operative Surgical Procedures; Outcome; Participant; Patients; Persons; Population; Population Analysis; Prevalence; Process; Publications; Race; Research; Research Personnel; Resources; Risk; Risk Factors; Series; Site; Source; Statistical Methods; Stochastic Processes; Subgroup; Text; Therapeutic; Time; Time trend; Universities; advanced analytics; age related; analytical method; analytical tool; base; burden of illness; clinical data warehouse; comorbidity; data resource; data warehouse; dementia risk; disorder risk; evidence base; health data; health disparity; health record; innovation; interest; live stream; mortality; multiple chronic conditions; news; population health; prospective; social; web site

Abstract Two of a series of in-person workshops in 2020-2022 will be hosted at Duke to provide new knowledge on how existing and recently developed analytic methods can be used for detailed population and clinical data analysis in order to make progress in understanding the causes and mechanisms of health-related disparities in Alzheimer’s disease (AD), related dementias (ADRD), and other prominent age-related diseases. The long- term goal of the series is to provide a resource focused on diffusing methodological know-how in terms of demonstrating the capabilities of newly developed methodologies, expanding on the rigor and range of application of well-established and familiar methods, promoting correct use of big health data both from a methodological and ethical prospective as well as providing a forum for experts and newcomers interested in health disparities and age-related diseases to discuss their ideas and promote their research. The pilot Duke- NIA workshop of the series held in February 2019 at Duke University was successful in drawing broad scientific interest to the topic and generated the background for the current proposal. The focus of the first workshop (planned in Winter 2020/2021) will be on demonstrating how studies using established administrative health data resources such as the Medicare claims database combined with innovative analytic approaches such as partitioning analyses, time-series based methods of projection/forecasting, and stochastic process models can be used to uncover previously overlooked and/or understudied aspects in this area of research. Specific topics to be discussed will include: i) disparities in risks and survival of AD/ADRD and other age- related diseases; ii) forecasting approaches for prevalence and mortality of AD/ADRD and other age-related diseases; iii) analysis of Medicare and other administrative claim-based data. The focus of the second workshop (planned in Winter 2021/2022) will extend this to include the health records data routinely collected in hospitals or University medical centers (e.g., the Duke Clinical Data Warehouse) and demonstrate how well- established and new analytic methods can be rigorously applied to such data to contribute to identifying the causes of persistent health disparities between specific groups of the U.S. population and narrowly defined patient strata. Specific topics will be expanded to include: i) analytic approaches to identify and quantify the contribution of treatment-related and medical care access-related factors to disparities in outcomes of AD/ADRD and other age-related diseases; ii) comorbidity, multimorbidity, treatment-related, social and genetic factors as sources of disparities in health outcomes of AD/ADRD and other age-related diseases; iii) forecasting of health outcomes and approaches for analyses of potential health interventions. The proceedings will be streamed live on the workshop website and presentations will be freely available in text and video form after the fact.

摘要 2020-2022年的一系列面对面研讨会中的两个将在杜克举办，以提供有关如何 现有的和最近开发的分析方法可用于详细的人群和临床数据分析 为了在了解与健康有关的差异的原因和机制方面取得进展， 阿尔茨海默病（AD）、相关痴呆（ADRD）和其他突出的年龄相关疾病。很长的- 该系列的长期目标是提供一个资源，重点是传播方法学知识， 展示新开发的方法的能力，扩大 应用成熟和熟悉的方法，促进正确使用大健康数据， 方法和道德前景，并为感兴趣的专家和新来者提供一个论坛 健康差距和与年龄有关的疾病，讨论他们的想法，促进他们的研究。飞行员杜克- 2019年2月在杜克大学举办的NIA系列研讨会成功地吸引了广泛的 科学界对这一专题的兴趣，并为目前的提案提供了背景。第一个的焦点 研讨会（计划在冬季2020/2021）将展示如何使用现有的行政管理研究 医疗保险索赔数据库等健康数据资源与创新的分析方法相结合 例如分区分析、基于时间序列的预测/预测方法和随机过程 模型可用于揭示该研究领域中以前被忽视和/或研究不足的方面。 将讨论的具体主题包括：i）AD/ADRD和其他年龄组的风险和生存率差异- ii）AD/ADRD和其他年龄相关疾病的患病率和死亡率的预测方法 疾病; iii）分析医疗保险和其他基于行政索赔的数据。第二个重点 研讨会（计划于2021/2022年冬季举行）将扩大这一范围，以包括定期收集的健康记录数据 在医院或大学医疗中心（例如，杜克临床数据仓库），并展示如何以及- 建立和新的分析方法可以严格适用于这些数据，以有助于确定 美国特定人群之间持续存在健康差异的原因， 患者分层。具体专题将扩大到包括：一）确定和量化 治疗相关因素和医疗服务获得相关因素对 AD/ADRD和其他年龄相关疾病; ii）合并症、多发病、治疗相关、社会和遗传 作为AD/ADRD和其他年龄相关疾病健康结果差异来源的因素; iii） 预测健康结果和分析潜在健康干预措施的方法。诉讼 将在研讨会网站上进行现场直播，并将以文字和视频形式免费提供演讲 在事后